A Novel and Efficient Bayesian Optimization Approach for Analog Designs with Multi-Testbench

Jingyao Zhao, Changhao Yan, Zhaori Bi, Fan Yang 0001, Xuan Zeng 0001, Dian Zhou. A Novel and Efficient Bayesian Optimization Approach for Analog Designs with Multi-Testbench. In 27th Asia and South Pacific Design Automation Conference, ASP-DAC 2022, Taipei, Taiwan, January 17-20, 2022. pages 86-91, IEEE, 2022. [doi]

@inproceedings{ZhaoYB00Z22,
  title = {A Novel and Efficient Bayesian Optimization Approach for Analog Designs with Multi-Testbench},
  author = {Jingyao Zhao and Changhao Yan and Zhaori Bi and Fan Yang 0001 and Xuan Zeng 0001 and Dian Zhou},
  year = {2022},
  doi = {10.1109/ASP-DAC52403.2022.9712590},
  url = {https://doi.org/10.1109/ASP-DAC52403.2022.9712590},
  researchr = {https://researchr.org/publication/ZhaoYB00Z22},
  cites = {0},
  citedby = {0},
  pages = {86-91},
  booktitle = {27th Asia and South Pacific Design Automation Conference, ASP-DAC 2022, Taipei, Taiwan, January 17-20, 2022},
  publisher = {IEEE},
  isbn = {978-1-6654-2135-5},
}